Advertisement

Water, Air, & Soil Pollution

, 229:343 | Cite as

Pollution of Arctic Waters Has Reached a Critical Point: an Innovative Approach to This Problem

  • Costas A. VarotsosEmail author
  • Vladimir F. Krapivin
Article

Abstract

One of the most important problems in the Arctic Basin is the pollution of its waters and the assessment of its impact on the ecological system of this region. In this paper, we recommend using the geoecological information-modeling system (GIMS) as one of the Big Data tools to address this problem. Specifically, the GIMS includes a series of specific models describing ecological, hydrological, climatic, and hydrochemical processes in Arctic waters. The synthesis of GIMS with the Arctic Basin Ecosystem (ABE) model provides the GIMS-ABE coupled model that takes into account various sources of pollutants, including river runoffs, long-range atmospheric transport, and anthropogenic activities in the coastal zone, as well as ships. In the simulation experiments performed in the present study, heavy metals, oil hydrocarbons, and radionuclides are considered as primary contaminants. In addition, the biocomplexity and survivability indicators were considered as information values to predict the status of the Arctic ecosystem. The results showed a high sensitivity of the Arctic ecosystem to pollution that is currently close to a tipping point. In particular, it emerged that the current state of pollution intensity leads to increased accumulation of pollutants in marine waters at different rates ranging from 7 to 23% depending on the Arctic aquatic environment.

Keywords

Arctic Basin Water pollution Contaminants Anthropogenic activities Modeling 

Notes

Funding Information

The study was supported by the scientists and staff of the Russian Fund for Fundamental Researches (Grant No. 16-01-00213) and the National and Kapodistrian University of Athens (Cooperative Agreement from 25 May 2017).

References

  1. Aksenov, Y. (2016). Arctic pathways of Pacific water: Arctic Ocean model intercomparison experiments. Journal of Geophysical Research. Oceans, 121(1), 27–59.CrossRefGoogle Scholar
  2. Aksenov, Y., & Coward, A. C. (2001). The Arctic Ocean circulation as simulated in a very high-resolution global ocean model (OCCAM). Annals of Glaciology, 33, 567–576.CrossRefGoogle Scholar
  3. AMAP. (2009). Radioactivity in the Arctic. Oslo: Arctic Monitoring and Assessment Programme 92 pp.Google Scholar
  4. Antcibor, I., Eschenbach, A., Zubrzycki, S., Kutzbach, L., Bolshiyanov, D., & Pfeiffer, E.-M. (2014). Trace metal distribution in pristine permafrost-affected soils of the Lena River delta and its hinterland, northern Siberia, Russia. Biogeosciences, 11, 1–15.CrossRefGoogle Scholar
  5. Bobylev, L. P., Kondratyev, K. Y., & Johannessen, O. M. (2003). Arctic environment variability in the context of global change. Chichester: Springer/Praxis 471 pp.Google Scholar
  6. Bring, A., Fedorova, I., Dibike, Y., Hinzman, L., Mård, J., Mernild, S. H., Prowse, T., Semenova, O., Stuefer, S. L., & Woo, M.-K. (2016). Arctic terrestrial hydrology: a synthesis of processes, regional effects, and research challenges. Journal of Geophysical Research, 121(3), 621–649.Google Scholar
  7. Chattopadhyay, S., Chattopadhyay, G., & Midya, S. K. (2018). Shannon entropy maximization supplemented by neurocomputing to study the consequences of a severe weather phenomenon on some surface parameters. Natural Hazards, 1–11.  https://doi.org/10.1007/s11069-018-3298-8.CrossRefGoogle Scholar
  8. Cheng B., Zhao J., & Vihma T. (2015). Detection of snow and ice thickness from temperature profiles of unmanned ice mass blance buoys. Proceedings of the 30th international symposium on Okhotsk Sea ans sea ice, 15–19 February 2015, Mombetsu, Hokkaido, Japan. The Okhotsk Sea & Cold Ocean Research Association, Mombetsu, Hokkaido, Japan, pp. 203–206.Google Scholar
  9. Cousteau, J. Y. (1963). The living sea. Paris: Harper Collins 325 pp.Google Scholar
  10. Cracknell, A. P., & Varotsos, C. A. (2007). Editorial and cover: fifty years after the first artificial satellite: from sputnik 1 to Envisat. International Journal of Remote Sensing, 28(10), 2071–2072.CrossRefGoogle Scholar
  11. Cracknell, A. P., & Varotsos, C. A. (2011). New aspects of global climate-dynamics research and remote sensing. International Journal of Remote Sensing, 32(3), 579–600.CrossRefGoogle Scholar
  12. Cracknell, A. P., Krapivin, V. F., & Varotsos, C. A. (2009). Global climatology and ecodynamics: anthropogenic changes to planet earth. Chichester: Springer/Praxis 518 pp.CrossRefGoogle Scholar
  13. Dementyev, D., Bolsunovsky, A., Borisov, R., & Trofimova, E. (2015). Concentrations of heavy metals in bottom sediments of the Yenisey River near Krasnoyarsk. Bulletin of the Tomsk Politechnic University, 326(5), 91–98 [in Russian].Google Scholar
  14. Duarte, C. M., Agustí, S., Wassmann, P., Arrieta, J. M., Alcaraz, M., Coello, A., Marbà, N., Hendriks, I. E., Holding, J., García-Zarandona, I., Kritzberg, E., & Vaqué, D. (2012). Tipping elements in the Arctic marine ecosystem. Ambio, 41(1), 44–55.CrossRefGoogle Scholar
  15. Efstathiou, M. N., & Varotsos, C. A. (2010). On the altitude dependence of the temperature scaling behaviour at the global troposphere. International Journal of Remote Sensing, 31(2), 343–349.CrossRefGoogle Scholar
  16. Efstathiou, M. N., & Varotsos, C. A. (2012). Intrinsic properties of Sahel precipitation anomalies and rainfall. Theoretical and Applied Climatology, 109(3–4), 627–633.CrossRefGoogle Scholar
  17. Efstathiou, M. N., & Varotsos, C. A. (2013). On the 11 year solar cycle signature in global total ozone dynamics. Meteorological Applications, 20(1), 72–79.CrossRefGoogle Scholar
  18. Fernández-Méndez, M., Katlein, C., Rabe, B., Nicolaus, M., Peeken, I., Bakker, K., Flores, H., & Boetius, A. (2015). Photosynthetic production in the Central Arctic Ocean during the record sea-ice minimum in 2012. Biogeosciences, 12, 3525–3549.CrossRefGoogle Scholar
  19. Fisher J. A. (2011). Atmospheric pollution in the Arctic: sources, transport, and chemical processing. Doctor of Philosophy Dissertation, Harvard University. The Department of Earth and Planetary Sciences, Cambridge, Massachusetts, 148 pp.Google Scholar
  20. Fouest, V. L., Babin, M., & Tremblay, J.-E. (2013). The fate of riverine nutrients on Arctic shelves. Biogeosciences, 10, 3661–3677.CrossRefGoogle Scholar
  21. Harms, I. H., Karcher, M. J., & Dethleff, D. (2000). Modelling Siberian river runoff—implications for contaminant transport in the Arctic Ocean. Journal of Marine Systems, 27, 95–115.CrossRefGoogle Scholar
  22. Hölemann, J. A., Schirmacher, M., & Prange, A. (2005). Seasonal variability of trace metals in the Lena River and the southeastern Laptev Sea: impact of the spring freshet. Global and Planetary Change, 48, 112–125.CrossRefGoogle Scholar
  23. Johannessen, O. M., Volkov, V. A., Pettersson, L. H., Maderich, V. S., Zheleznyak, M. J., Gao, Y., Bobylev, L. P., Stepanov, A. V., Neelov, I. A., Tishkov, V. P., & Nielsen, S. P. (2010). Radioactivity and pollution in the Nordic seas and Arctic region: Observations, modeling, and simulations. Chichester: Springer/Praxis 407 pp.CrossRefGoogle Scholar
  24. Kelley J. J. & Krapivin V. F. (2004). Biocomplexity problem related to the Okhotsk Sea fisheries. Proceedings of the international conference DAS, 27–29 June 2004, Suceava, Romania, pp. 52–57.Google Scholar
  25. Komuro, Y. (2014). The impact of surface mixing on the arctic river water distribution and stratification in a global Ice-Ocean model. Journal of Climate, 27, 4359–4370.CrossRefGoogle Scholar
  26. Kondratyev, K. Y., & Krapivin, V. F. (2001). Biocomplexity and global geographic information monitoring. Mapping Sciences and Remote Sensing, 38(4), 260–271.CrossRefGoogle Scholar
  27. Kondratyev, K. Y., & Varotsos, C. A. (2001). Global tropospheric ozone dynamics. Part II: numerical modelling of tropospheric ozone variability: part I: tropospheric ozone precursors. Environmental Science and Pollution Research, 8(2), 113–119.CrossRefGoogle Scholar
  28. Kondratyev, K. Y., Krapivin, V. F., & Phillips, G. W. (2002). Global environmental change: modelling and monitoring. Berlin: Springer-Verlag 319 pp.CrossRefGoogle Scholar
  29. Kondratyev, K. Y., Krapivin, V. F., & Phillips, G. W. (2003). Arctic Basin pollution dynamics. In L. P. Bobylev, K. Y. Kondratyev, & O. M. Johannessen (Eds.), Arctic environment variability in the context of global change (pp. 309–362). Chichester: Springer/Praxis.Google Scholar
  30. Kondratyev, K. Y., Ivlev, L. S., Krapivin, V. F., & Varotsos, C. A. (2006). Atmospheric aerosol properties: formation, Processes and Impacts. Chichester: Springer/PRAXIS 572 p.Google Scholar
  31. Krapivin, V. F. (1996). The estimation of the Peruvian current ecosustem by a mathematical model of biosphere. Ecological Modelling, 91, 1–14.CrossRefGoogle Scholar
  32. Krapivin, V. F., & Phillips, G. W. (2001). Application of a global model to the study of Arctic basin pollution: radionuclides, heavy metals and oil carbohydrates. Environmental Modeling and Software, 16, 1–17.CrossRefGoogle Scholar
  33. Krapivin, V. F., & Varotsos, C. A. (2007). Globalization and sustainable development. Chichester: Springer/Praxis 304 p.Google Scholar
  34. Krapivin, V. F., & Varotsos, C. A. (2008). Biogeochemical cycles in globalization and sustainable development. Chichester: Springer/Praxis 562 p.Google Scholar
  35. Krapivin, V. F., Cherepenin, V. A., Phillips, G. W., August, R. A., Pautkin, A. Y., Harper, M. J., & Tsang, F. Y. (1998). An application of modeling technology to the study of radionuclear pollutants and heavy metals dynamics in the Angara-Yenisey river system. Ecological Modelling, 111(2–3), 121–134.CrossRefGoogle Scholar
  36. Krapivin, V. F., Varotsos, C. A., & Soldatov, V. Y. (2015). New ecoinformatics tools in environmental science: applications and decision-making. London: Springer 903 pp.CrossRefGoogle Scholar
  37. Krapivin, V. F., Varotsos, C. A., & Soldatov, V. Y. (2017a). The Earth’s population can reach 14 billion in the 23rd century without significant adverse effects on survivability. The International Journal of Environmental Research and Public Health, 14(8), 3–18.CrossRefGoogle Scholar
  38. Krapivin, V. F., Varotsos, C. A., & Soldatov, V. Y. (2017b). Simulation results from a coupled model of carbon dioxide and methane global cycles. Ecological Modelling, 359, 69–79.CrossRefGoogle Scholar
  39. Lazaridou, M., Varotsos, C., Alexopoulos, K., & Varotsos, P. (1985). Point defect parameters of LiF. Journal of Physics C: Solid State Physics, 18(20), 3891.CrossRefGoogle Scholar
  40. Legendre L. & Krapivin V. F. (1992). Model for vertical structure of phytoplankton community in Arctic regions. Proceedings of the Seventh International Symposium on Okhotsk Sea and Sea Ice, 2-5 February 1992, Mombetsu, Hokkaido, Japan. Mombetsu, Hokkaido: Okhotsk Sea & Cold Ocean Research association, pp. 314–316.Google Scholar
  41. Legendre, P., & Legendre, L. (1998). Numerical ecology. Amsterdam: Elsevier 853 pp.Google Scholar
  42. Libes, S. (2009). Introduction to marine biochemistry. London: Elsevier 895 pp.Google Scholar
  43. Ma, J., Hung, H., Tian, C., & Kellenborn, R. (2011). Revolatilization of persistent organic pollutants in the Arctic induced by climate change. Nature Climate Change, 1, 255–260.CrossRefGoogle Scholar
  44. Mintzer, I. M. (1987). A matter of degrees: the potential for controlling the greenhouse effect. Washington: World Resources Institute Research Report No. 15 70 pp.Google Scholar
  45. Nagato, Y., & Tanaka, H. L. (2012). Global warming trend without the contributions from decadal variability of the Arctic oscillation. Polar Science, 6, 15–22.CrossRefGoogle Scholar
  46. Nakashima D. J., McLean G. K., Thulstrup H. D., Castillo R., & Rubis J. T. (2012). Weathering uncertainty: traditional knowledge for climate change assessment and adaptation. UNESCO, Paris and UNU, Darwin, 120 pp.Google Scholar
  47. Nikanorov, A. M., Bryzgalo, V. A., Kosmenko, L. S., & Reshetnyak, O. S. (2011). The Kolyma River mouth area under present conditions of anthropogenic impact. Russian Meteorology and Hydrology, 36(8), 549–558.CrossRefGoogle Scholar
  48. Nitu, C., Krapivin, V. F., & Dobrescu, A. S. (2010). Application of global model to the study of Arctic Basin pollution. Scientific Bulletin of the Electrical Engineering Faculty, 1(12), 111–114.Google Scholar
  49. Osabe T., Fukuda J., Hara T., Ohnishi F., Otsuka N., Saitoh S.-I., Sugimoto A., Takahashi M., Tanaka M., Tanaka S., & Yasunaga H. (2018). Future scenarios for Arctic 2050. Proceedings of the 33rd International Symposium on Okhotsk Sea & Polar Oceans 2018. 18–21 February 2018. Mombetsu, Hokkaido, Japan. Okhotsk Sea and Polar Oceans Research Association, Mombetsu, Hokkaido, Japan, 2018, pp. 117–118.Google Scholar
  50. Osipova, N. A., Stepanova, K. D., & Matveenko, I. A. (2015). Evaluation of metal content in perch of the Ob River basin. Earth and Environmental Science, 27, 1–5.Google Scholar
  51. Proshutinsky, A. Y., & Johnson, M. (2001). Two regimes of the Arctic’s circulation from ocean models with ice and comtaminants. Marine Pollution Bulletin, 43(1–6), 61–70.CrossRefGoogle Scholar
  52. Steehouwer, H. (2016). Ortec finance scenario approach. ORTeC Finance Scenario Department (p. 54). The Netherlands: Rotterdam.Google Scholar
  53. Steele, M., Ermold, W., & Zhang, J. (2011). Modeling the formation and fate of the near surface temperature maximum in the Canadian Basin of the Arctic Ocean. Journal of Geophysical Research, 116(C11015), 1–13.Google Scholar
  54. Stohl, A. (2004). Intercontinental transport of air pollution. London: Springer 326 pp.Google Scholar
  55. Stone, D. P. (2015). The changing Arctic environment: the Arctic messenger (Vol. 374, pp. 21–23). Cambridge: Cambridge University Press.Google Scholar
  56. Varotsos, C. (2002). The southern hemisphere ozone hole split in 2002. Environmental Science and Pollution Research, 9(6), 375–376.CrossRefGoogle Scholar
  57. Varotsos, C., & Cartalis, C. (1991). Re-evaluation of surface ozone over Athens, Greece, for the period 1901–1940. Atmospheric Research, 26(4), 303–310.CrossRefGoogle Scholar
  58. Varotsos, C. A., & Zellner, R. (2010). A new modeling tool for the diffusion of gases in ice or amorphous binary mixture in the polar stratosphere and the upper troposphere. Atmospheric Chemistry and Physics, 10(6), 3099–3105.CrossRefGoogle Scholar
  59. Varotsos, C. A., & Krapivin, V. F. (2017). A new big data approach based on geoecological information-modeling system. Big Earth Data, 1, 47–63.CrossRefGoogle Scholar
  60. Varotsos, C., Kondratyev, K. Y., & Katsikis, S. (1995). On the relationship between total ozone and solar ultraviolet radiation at St. Petersburg, Russia. Geophysical Research Letters, 22(24), 3481–3484.CrossRefGoogle Scholar
  61. Varotsos, C. A., Kondratyev, K. Y., & Cracknell, A. P. (2000). New evidence for ozone depletion over Athens, Greece. International Journal of Remote Sensing, 21(15), 2951–2955.CrossRefGoogle Scholar
  62. Varotsos, C. A., Efstathiou, M. N., & Cracknell, A. P. (2013). On the scaling effect in global surface air temperature anomalies. Atmospheric Chemistry and Physics, 13(10), 5243–5253.CrossRefGoogle Scholar
  63. Varotsos, C. A., Franzke, C. L., Efstathiou, M. N., & Degermendzhi, A. G. (2014). Evidence for two abrupt warming events of SST in the last century. Theoretical and Applied Climatology, 116(1–2), 51–60.CrossRefGoogle Scholar
  64. Wang, D., Hemrichs, S. M., & Guo, L. (2006). Distributions of nutrients, dissolved organic carbon and carbonhydrates in the western Arctic Ocean. Continental Shelf Research, 26(14), 1654–1667.CrossRefGoogle Scholar
  65. Williams, M., Eugster, W., Rastetter, E. B., McFadden, J. P., & Chapin III, F. S. (2000). The controls on net ecosystem productivity along an Arctic transect: a model comparison with flux measurements. Global Change Biology, 6(1), 116–126.CrossRefGoogle Scholar
  66. Xue, Y., Sellers, P. J., Kinter, J. L., & Shukla, J. (1991). A simplified biosphere model for global climate studies. Journal of Climate, 4(3), 345–364.CrossRefGoogle Scholar
  67. Zhang, Y., Lu, X., Wang, N., Xin, M., Geng, S., Jia, J., & Meng, G. (2016). Heavy metals in aquatic organisms of different trophic levels and their potential human health risk in Bohai Bay, China. Environmental Science and Pollution Research International, 23(17), 17801–17810.CrossRefGoogle Scholar
  68. Zweng M. M., Boyer T. P., Baranova O. K., Reagan J. R., Seidov D., & Smolyar I. V. (2017). An inventory of arctic ocean data in the world ocean database. Earth System Science. Data Discussions,  https://doi.org/10.5194/essd-2017-63.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Environmental Physics and MeteorologyNational and Kapodistrian University of AthensAthensGreece
  2. 2.Kotelnikov Institute of Radioengineering and ElectronicsRussian Academy of SciencesMoscowRussia

Personalised recommendations